Typeahead image generation

Abstract

A system and method for typeahead image generation are provided. The method may include receiving, via a user interface during a prompting session, a text prompt describing an image. The method also may include generating, via a trained diffusion model, the image representative of the text prompt. The method further may include determining, via the trained diffusion model, a reconciled risk score based on a determined risk score of the text prompt and a determined risk score of the generated image. The method even further may include causing, via the trained diffusion model in response to the determined reconciled risk score, to (i) approve the generated image in an instance in which the determined reconciled risk score meets or exceeds a predetermined threshold, or (ii) deny the generated image in an instance in which the determined reconciled risk score fails to meet the predetermined threshold.

What is claimed: 
     
         1 . A method comprising:
 receiving, via a user interface during a prompting session, a text prompt describing an image;   generating, via a trained diffusion model, the image representative of the text prompt;   determining, via the trained diffusion model, a reconciled risk score based on a determined risk score of the text prompt and a determined risk score of the generated image; and   causing, via the trained diffusion model in response to the determined reconciled risk score, to (i) approve the generated image in an instance in which the determined reconciled risk score meets or exceeds a predetermined threshold, or (ii) deny the generated image in an instance in which the determined reconciled risk score fails to meet the predetermined threshold.   
     
     
         2 . The method of  claim 1 , wherein the text prompt comprises a seed indicating a constant attribute associated with the image for a duration of the prompting session. 
     
     
         3 . The method of  claim 1 , further comprising:
 transmitting, via the user interface, an indication to enhance the received text prompt describing the image.   
     
     
         4 . The method of  claim 1 , wherein:
 the text prompt comprises a first text prompt and a second text prompt; and   the generated image of the second text prompt is different from the generated image of the first text prompt.   
     
     
         5 . The method of  claim 1 , further comprising:
 prior to transmitting the text prompt to the trained diffusion model, determining the text prompt comprises a threshold number of characters.   
     
     
         6 . The method of  claim 5 , wherein the determining the text prompt comprises evaluating the text prompt for one or more characters indicating insufficient data to generate the image. 
     
     
         7 . The method of  claim 5 , wherein the determining the text prompt comprises monitoring a predetermined amount of time elapsed after receiving the text prompt. 
     
     
         8 . The method of  claim 1 , further comprising:
 causing the approved generated image to be displayed on the user interface.   
     
     
         9 . The method of  claim 1 , wherein the denial is a discard or a hold of the generated image. 
     
     
         10 . The method of  claim 1 , wherein the trained diffusion model is located on a server operably coupled to the user interface. 
     
     
         11 . The method of  claim 8 , wherein the trained diffusion model comprises a trained student diffusion model distilled with any one or more of backward distillation, shifted reconstruction loss, or noise correction. 
     
     
         12 . A system comprising:
 a non-transitory memory comprising instructions stored thereon; and   at least one processor, operably coupled to the non-transitory memory, configured to execute the instructions comprising:
 receiving, via a user interface during a prompting session, a text prompt describing an image; 
 generating, via a trained diffusion model, the image representative of the text prompt; 
 determining, via the trained diffusion model, a reconciled risk score based on a determined risk score of the text prompt and a determined risk score of the generated image; and 
 causing, via the trained diffusion model in response to the determined reconciled risk score, to (i) approve the generated image in an instance in which the determined reconciled risk score meets or exceeds a predetermined threshold, or (ii) deny the generated image in an instance in which the determined reconciled risk score fails to meet the predetermined threshold. 
   
     
     
         13 . The system of  claim 12 , wherein the text prompt comprises a seed indicating a constant attribute associated with the image for a duration of the prompting session. 
     
     
         14 . The system of  claim 12 , wherein the at least one processor is further configured to execute the instructions of:
 transmitting, via the user interface, an indication to enhance the received text prompt describing the image.   
     
     
         15 . The system of  claim 12 , wherein:
 the text prompt comprises a first text prompt and a second text prompt; and   the generated image of the second text prompt is different from the generated image of the first text prompt.   
     
     
         16 . The system of  claim 12 , wherein the at least one processor is further configured to execute the instructions of:
 prior to transmitting the text prompt to the trained diffusion model, determining the text prompt comprises a threshold number of characters.   
     
     
         17 . The system of  claim 16 , wherein the determining the text prompt comprises evaluating the text prompt for one or more characters indicating insufficient data to generate the image. 
     
     
         18 . The system of  claim 16 , wherein the determining the text prompt comprises monitoring a predetermined amount of time elapsed after receiving the text prompt. 
     
     
         19 . A non-transitory computer readable medium comprising stored instructions that when executed effectuates:
 receiving, via a user interface during a prompting session, a text prompt describing an image;   generating, via a trained diffusion model, the image representative of the text prompt;   determining, via the trained diffusion model, a reconciled risk score based on a determined risk score of the text prompt and a determined risk score of the generated image; and   causing, via the trained diffusion model in response to the determined reconciled risk score, to (i) approve the generated image in an instance in which the determined reconciled risk score meets or exceeds a predetermined threshold, or (ii) deny the generated image in an instance in which the determined reconciled risk score fails to meet the predetermined threshold.   
     
     
         20 . The non-transitory computer readable medium of  claim 19 , wherein the stored instructions when executed further effectuates:
 causing the approved generated image to be displayed on the user interface.